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PseudotimeDE: inference of differential gene expression along cell pseudotime with well-calibrated p-values from single-cell RNA sequencing data
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PseudotimeDE: inference of differential gene expression along cell pseudotime with well-calibrated p-values from single-cell RNA sequencing data
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Journal Article
PseudotimeDE: inference of differential gene expression along cell pseudotime with well-calibrated p-values from single-cell RNA sequencing data
2021
Overview
To investigate molecular mechanisms underlying cell state changes, a crucial analysis is to identify differentially expressed (DE) genes along the pseudotime inferred from single-cell RNA-sequencing data. However, existing methods do not account for pseudotime inference uncertainty, and they have either ill-posed
p
-values or restrictive models. Here we propose PseudotimeDE, a DE gene identification method that adapts to various pseudotime inference methods, accounts for pseudotime inference uncertainty, and outputs well-calibrated
p
-values. Comprehensive simulations and real-data applications verify that PseudotimeDE outperforms existing methods in false discovery rate control and power.
Publisher
BioMed Central,Springer Nature B.V,BMC
Subject
/ Animal Genetics and Genomics
/ Biomedical and Life Sciences
/ Computational Biology - methods
/ Datasets
/ Gene Expression Profiling - methods
/ Gene Expression Regulation, Developmental
/ genes
/ High-Throughput Nucleotide Sequencing
/ Method
/ Methods
/ Microbial Genetics and Genomics
/ Organ Specificity - genetics
/ Power
/ RNA
/ Sequence Analysis, RNA - methods
/ Single-Cell Analysis - methods
/ Values
